The paper "Applying Financial Distress Prediction Models in Saudi Arabia Businesses" is a great example of a business research proposal. The financial impact of business failure is colossal, especially affecting the interest of the stakeholders of various publically traded companies. Research has indicated that prior to undergoing business failure the company’ s financial position is commonly under distress. Thus, it is essential to identify these financial distresses at the early stages itself so that the stakeholders and investors interest could be safeguarded (Dothan 2006). The recent global recession has also exposed the vulnerability of various established companies throughout the world.
The recession has even left a dent on the perceived stabilised economy and business of Saudi Arabia as well (Cerra et al 2009). Therefore, the proposed research focuses on using various statistical models to predict financial distress in Saudi Arabian companies, which can help in identifying such a negative economic situation in the future and preventing them. In order to conduct this research, data from around 30 listed companies would be collected and analysed. Further, a structured questionnaire would also be designed to extract the necessary information from these companies.
The collected data would be analysed using various statistical techniques such as Logistic regression, Linear Discriminant Analysis and Artificial Neural Network. Further, a model would be created to predict financial distress in these companies. The proposed model would be based on predicting distress on the basis of liquidity, debt, profitability and other such variables. The statistical results for this model would help in identifying and predicting financial distress in companies, which would help in controlling financial losses at the onset of financial troubles in a company. Aim An essential asset to any business, particularly those related to financial investment and lending, is a reliable and accurate Business Failure Prediction (BFP) model.
Such models are of immense benefit, especially in times of financial instability where new business ventures can be precarious. Therefore, there has been a substantial increase in interest in the area of business failure prediction, from both industry and academia as it helps in recognising the benefits and associated value that these models can offer to all sectors concerned. In Saudi Arabia, there is a growing need for an established and accurate business failure model especially for those related to family businesses, as this is the most common type of business found in the country.
In the present global financial climate, this need is emphasised by the current lack of literature and the continued emphasis for viable models that would be operable in the real world. This project would focus on developing such a business failure prediction model using the available resources that highlight the past and current research, as well as the key factors involved when investigating family businesses in Saudi Arabia. Thus, the project aims to: Develop a business failure model for Saudi Arabia business, and particularly family-owned businesses Amend and develop the existing literature to make it suitable for businesses in Saudi Arabia with an Islamic finance focus Investigate whether the companies based on Islamic financial system are more subject to financial distress in comparison with other companies based on a conventional system.
Altman, E. “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy.” The Journal of Finance 22 (1968): 589-609.
Altman, E., Hotchkiss, E. “Corporate Financial Distress and Bankruptcy: Predict and Avoid Bankruptcy, Analyze and Invest in Distressed Debt.” 3rd Edition, New Jersey: John Wiley & Sons (2005).
Beaver, W. Financial Ratios as Predictors of Failure. Journal of Accounting Research 5 (1966): 71-111.
Bradley, J. R. "Saudi Arabia exposed: Inside a kingdom in crisis." New York: Palgrave Macmillan (2005).
Brealey, R., Meyers, S. “Principles of Corporate Finance.” 6th Edition, McGraw-Hill, New York (2000).
Brown, G., Kapadia, N. “Firm-Specific Risk and Equity Market Development.” Journal of Financial Economics 84 (2007), 358-388.
Cerra, V., Panizza, U. and Saxena, S. “International Evidence on Recovery from Recessions.” IMF Working Paper 09/183 (2009). Washington: International Monetary Fund.
Clarke, F., G. Dean and K. Oliver. “Corporate Collapse: Accounting, Regulatory and Ethical Failure”. Cambridge University Press. 2003.
Damodaran, A. Investment Valuation. 2nd Edition, New York: Wiley Finance (2002).
DePamphilis, M. “Mergers, Acquisitions, and Other Restructuring Activities.” 5th edition (2009).
Dothan, M. “Costs of Financial Distress and Interest Coverage Ratios.” The Journal of Financial Research 29 (2006): 147-162.
Fletcher, D and Goss , E. “Forecasting with neural Network: an application using bankruptcy data”. Information and Management 24 (1993): 159-167.
Giesecke, K. “Default and Information.” Journal of Economic Dynamics and Control, 2005.
Habbershon, Timothy G. and Williams Mary l. “A Resource-based Framework for Assessing the Strategic Advantage of Family Firms.” Family Business Review 12 (1999): 1-25.
Hyvari, I. ‘‘Success of projects in different organizational conditions’’. Project Management Journal 37(2006): 31-41.
Kahl, M. “Economic Distress, Financial Distress, and Dynamic Liquidation.” The Journal of Finance 57 (2002): 135-168.
Kumar, K and Ganesalingam S. “Detection of Financial Distress using Multivariate Methods. Managerial Finance (MCB University Press)”. Special Issue edited by K. Kumar, Vol.27, No5, (2001): 45-55.
Mahayny, K. “Difficulties Facing Family Owned Businesses in the Arab Region”. A paper presented to the conference “Business Development & Family Businesses: Managerial Foundations & International Accounting Standards”, Arab Tax Society, Cairo, Egypt (2007), 10-11 February, Nile Hilton.
Martin, Daniel. “Early Warning of Bank Failure: A Logit Regression Approach”. Journal of Banking and Finance (1977): 249-276.
Ohlson, J. “Financial Ratios and Probabilistic Prediction of Bankruptcy.” Journal of Accounting Research 18 (1980): 109-131.
Pindado, J. and Rodrigues, L. “Determinants of Financial Distress Costs.” Financial Markets and Portfolio Management 19 (2005): 343-359.
Reinhart, C.M. and Rogoff, K.S. “The Aftermath of Financial Crises”. American Economic Review (2009). American Economic Association, Pittsburgh, PA.
Sori, Z. M. and Jalil, H. A. “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Distress”. Journal of Money, Investment and Banking 2009: 5-15.
Tan, C N W. “ANN application in financial Distress prediction and Foreign exchange trading”. Whilberto Publishing, Gold Coast, Australia. 2001.
White, G. B. “Perceptions Of Accountants: What Are They After Enron And WorldCom?” Journal of College Teaching & Learning 3 (2006): 71-76.
Zurada, J. “Neural Networks Versus Logit Regression Models for Predicting Financial Distress Response Variables.” The Journal of Applied business Research 15(1998): 21-28.